Standard deviation in the # of neurons per layer
Input layers will always have the dimensionality of your input data(for every model I can think of).
See above, the deviation between hidden layers can be significant. For example, 128 in the first hidden and 64 in the rest(or vice versa).
This question in particular will always be problem dependent. It is decided via architecture search or intuition/experience combined with some exploratory search.